The present invention relates generally to image processing, and more particularly, but not by way of limitation, relating a system, a method, and a recording medium including of two or more videos taken of a scene at different times and determining a change event (i.e., discrepancy) of detection between the two or more videos.
UAVs (Unmanned Aerial Vehicles) and bodycams are emerging as de facto imaging method for many applications including defense, surveillance, asset management. Surveillance and reconnaissance tasks are currently often performed using an airborne platform such as a UAV. The airborne platform can carry different sensors. EO/IR cameras can be used to view a certain area from above. To support the task from the sensor analyst, different image processing techniques can be applied on the data, both in real-time or for forensic applications. Effective summarization of view of the multiple cameras on an (unmanned) aerial vehicle is of great importance in such uses. Additionally, a method of stitching images provided by such UAVs is needed.
Stitching images for use in visual analytic business is of great importance. For example, creating a panoramic view from video sequences from multiple cameras is a critical component for many analytic applications including defense, surveillance, asset management.
Algorithms for aligning and stitching images into seamless photo-mosaics are widely used in computer vision. One of the most important aspects of image stitching is to seamlessly blend overlapping images, even in the presence of parallax, lens distortion, and different scene illuminations, to provide a mosaic without any artifacts and that looks as natural as possible. Evidently, there is some subjectivity in interpreting how natural a panorama or a mosaic looks. Furthermore, the stitching techniques must be able to extrapolate well to the regions of the panorama where there is information only from a single image.
Therefore, it is desirable to provide an improved way to detect a discrepancy between a plurality of videos captured of a same scene at different times and the stitched images thereof to provide the discrepancy between the videos as an output.